Maintenance Decision-Making for Sluice Gate Facilities Based on Carbonation-Based Residual Service Life Prediction and Risk-Weighting Scenario Analysis

With the increasing frequency of floods associated with climate change and the ongoing aging of river infrastructure, hydraulic gate facilities must maintain both structural integrity and reliable operational functionality, such as gate opening and closing performance. Accordingly, maintenance decision-making requires assessment approaches that comprehensively evaluate both the physical condition and functional performance of these facilities. Although the current overall grade-based assessment system serves as a management tool by integrating inspection data with standardized evaluation procedures, it has limitations in adequately distinguishing between the deterioration characteristics associated with physical service-life and the degradation of functional performance within the evaluation process. This study analyzed detailed safety inspection data from 51 hydraulic gate facilities within the target watershed and proposed a prioritization model that separately assesses structural durability risk and operational functional risk. Physical condition was quantified by predicting the remaining service life based on carbonation using the Tuutti model, and scenario analysis incorporating varying weighting factors for mechanical equipment importance was conducted to examine variability in maintenance prioritization. The results indicate that approximately 16% of the facilities received relatively favorable overall condition grades despite exhibiting degraded mechanical performance. Sensitivity analysis further revealed that priority inversion between structurally aged facilities and mechanically aged facilities occurred when the weighting factor assigned to mechanical equipment risk exceeded approximately 45%. The integrated priority index (PI) and the weighting-based scenario analysis proposed in this study provide a quantitative framework for maintenance prioritization and are expected to support maintenance budget planning by enabling management authorities to systematically incorporate facility-specific structural and functional condition characteristics into the decision-making process.